{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 人脸识别与计算机视觉文档实践\n",
    "\n",
    ">* 本周主要内容：人脸（Face） API文档不同平台对比与实践及计算机视觉入门（认知服务）\n",
    ">* 202009_API_人工智能与机器学习_week03\n",
    ">*  电子讲义设计者：许智超\n",
    "<br/>\n",
    "<br/>\n",
    "\n",
    "## 复习\n",
    "\n",
    "* 上周主要内容： \n",
    ">    * 1、API文档\n",
    ">    * 2、认知服务-人脸识别\n",
    ">    * 3、pandas黑魔法（json_normalize）\n",
    "-----\n",
    "* 提问、检查与扩展：\n",
    ">    * 1、上周的Azure face API随机检查2位同学，对于API文档是否有能力详细阅读？\n",
    ">    * 2、抽查2位同学，对于获取的数据用途有何思考？是否尝试其他平台（XXX API、XXX API）      \n",
    ">    * 3、扩展: 我们尝试抽取了4张图片，包含AB、ABC、BCD、ABCD四个人物特征，如何通过API检查数据差异？\n",
    "  \n",
    "\n",
    "-----\n",
    "## 本周学习目标：\n",
    "\n",
    "> $\\mathcal{1、Azure 认知服务-人脸集合演示}$     \n",
    "> $\\mathcal{2、Face++ 之 FaceSets 实践}$     \n",
    "> $\\mathcal{3、计算机视觉实践}$    \n",
    "\n",
    "\n",
    "\n",
    "## 学生权限\n",
    "\n",
    "* [访问学生权益](https://azure.microsoft.com/zh-cn/education/)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "/* 本电子讲义使用之CSS */\n",
       "div.code_cell {\n",
       "    background-color: #e5f1fe;\n",
       "}\n",
       "div.cell.selected {\n",
       "    background-color: #effee2;\n",
       "    font-size: 2rem;\n",
       "    line-height: 2.4rem;\n",
       "}\n",
       "div.cell.selected .rendered_html table {\n",
       "    font-size: 2rem !important;\n",
       "    line-height: 2.4rem !important;\n",
       "}\n",
       ".rendered_html pre code {\n",
       "    background-color: #C4E4ff;   \n",
       "    padding: 2px 25px;\n",
       "}\n",
       ".rendered_html pre {\n",
       "    background-color: #99c9ff;\n",
       "}\n",
       "div.code_cell .CodeMirror {\n",
       "    font-size: 2rem !important;\n",
       "    line-height: 2.4rem !important;\n",
       "}\n",
       ".rendered_html img, .rendered_html svg {\n",
       "    max-width: 50%;\n",
       "    height: auto;\n",
       "    float: center;\n",
       "}\n",
       "/* Gradient transparent - color - transparent */\n",
       "hr {\n",
       "    border: 0;\n",
       "    border-bottom: 1px dashed #ccc;\n",
       "}\n",
       ".emoticon{\n",
       "    font-size: 5rem;\n",
       "    line-height: 4.4rem;\n",
       "    text-align: center;\n",
       "    vertical-align: middle;\n",
       "}\n",
       "\n",
       "</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<style>\n",
    "/* 本电子讲义使用之CSS */\n",
    "div.code_cell {\n",
    "    background-color: #e5f1fe;\n",
    "}\n",
    "div.cell.selected {\n",
    "    background-color: #effee2;\n",
    "    font-size: 2rem;\n",
    "    line-height: 2.4rem;\n",
    "}\n",
    "div.cell.selected .rendered_html table {\n",
    "    font-size: 2rem !important;\n",
    "    line-height: 2.4rem !important;\n",
    "}\n",
    ".rendered_html pre code {\n",
    "    background-color: #C4E4ff;   \n",
    "    padding: 2px 25px;\n",
    "}\n",
    ".rendered_html pre {\n",
    "    background-color: #99c9ff;\n",
    "}\n",
    "div.code_cell .CodeMirror {\n",
    "    font-size: 2rem !important;\n",
    "    line-height: 2.4rem !important;\n",
    "}\n",
    ".rendered_html img, .rendered_html svg {\n",
    "    max-width: 50%;\n",
    "    height: auto;\n",
    "    float: center;\n",
    "}\n",
    "/* Gradient transparent - color - transparent */\n",
    "hr {\n",
    "    border: 0;\n",
    "    border-bottom: 1px dashed #ccc;\n",
    "}\n",
    ".emoticon{\n",
    "    font-size: 5rem;\n",
    "    line-height: 4.4rem;\n",
    "    text-align: center;\n",
    "    vertical-align: middle;\n",
    "}\n",
    "\n",
    "</style>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 复习\n",
    "\n",
    "> 1、回顾阅读API文档的关键点     \n",
    "> 2、正确阅读json数据 [jsonviewer.stack.hu(json转换检查数据)](http://jsonviewer.stack.hu)    \n",
    "> 3、pandas 中的json_normalize模块/函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A-1 面部检测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[{\"faceId\": \"670f1e49-3f7c-41f7-9f24-0530aeae0457\", \"faceRectangle\": {\"top\": 69, \"left\": 341, \"width\": 124, \"height\": 124}, \"faceAttributes\": {\"smile\": 1.0, \"headPose\": {\"pitch\": 8.7, \"roll\": 29.8, \"yaw\": 5.0}, \"gender\": \"male\", \"age\": 22.0, \"facialHair\": {\"moustache\": 0.1, \"beard\": 0.1, \"sideburns\": 0.1}, \"glasses\": \"NoGlasses\", \"emotion\": {\"anger\": 0.0, \"contempt\": 0.0, \"disgust\": 0.0, \"fear\": 0.0, \"happiness\": 1.0, \"neutral\": 0.0, \"sadness\": 0.0, \"surprise\": 0.0}, \"blur\": {\"blurLevel\": \"low\", \"value\": 0.1}, \"exposure\": {\"exposureLevel\": \"overExposure\", \"value\": 0.8}, \"noise\": {\"noiseLevel\": \"medium\", \"value\": 0.64}, \"makeup\": {\"eyeMakeup\": true, \"lipMakeup\": true}, \"accessories\": [], \"occlusion\": {\"foreheadOccluded\": false, \"eyeOccluded\": false, \"mouthOccluded\": false}, \"hair\": {\"bald\": 0.02, \"invisible\": false, \"hairColor\": [{\"color\": \"brown\", \"confidence\": 1.0}, {\"color\": \"black\", \"confidence\": 0.94}, {\"color\": \"red\", \"confidence\": 0.18}, {\"color\": \"gray\", \"confidence\": 0.11}, {\"color\": \"blond\", \"confidence\": 0.1}, {\"color\": \"other\", \"confidence\": 0.07}, {\"color\": \"white\", \"confidence\": 0.0}]}}}]'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A-1 面部检测\n",
    "import requests\n",
    "import json\n",
    "\n",
    "# set to your own subscription key value\n",
    "subscription_key = \"22860f2ec4fa40668703f86a97b571b6\"\n",
    "assert subscription_key\n",
    "\n",
    "# replace <My Endpoint String> with the string from your endpoint URL\n",
    "face_api_url = 'https://chick.cognitiveservices.azure.com/face/v1.0/detect'\n",
    "\n",
    "# 请求正文body\n",
    "image_url = 'https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603391956426&di=c8f7f01de1249fa11649d7e45ca04517&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20180205%2F1e7e0127a60a481f86d7de0633ac42bf.jpeg'\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': subscription_key}\n",
    "\n",
    "# 请求参数parameters\n",
    "params = {\n",
    "    'returnFaceId': 'true',\n",
    "    'returnFaceLandmarks': 'false',\n",
    "    # 可选参数,请仔细阅读API文档\n",
    "    'returnFaceAttributes': 'age,gender,headPose,smile,facialHair,glasses,emotion,hair,makeup,occlusion,accessories,blur,exposure,noise',\n",
    "}\n",
    "\n",
    "response = requests.post(face_api_url, params=params,\n",
    "                         headers=headers, json={\"url\": image_url})\n",
    "# json.dumps 将json--->bytes\n",
    "json.dumps(response.json())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A-2 json转译\n",
    "\n",
    "> * bytes ---> json\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'faceId': '670f1e49-3f7c-41f7-9f24-0530aeae0457',\n",
       "  'faceRectangle': {'top': 69, 'left': 341, 'width': 124, 'height': 124},\n",
       "  'faceAttributes': {'smile': 1.0,\n",
       "   'headPose': {'pitch': 8.7, 'roll': 29.8, 'yaw': 5.0},\n",
       "   'gender': 'male',\n",
       "   'age': 22.0,\n",
       "   'facialHair': {'moustache': 0.1, 'beard': 0.1, 'sideburns': 0.1},\n",
       "   'glasses': 'NoGlasses',\n",
       "   'emotion': {'anger': 0.0,\n",
       "    'contempt': 0.0,\n",
       "    'disgust': 0.0,\n",
       "    'fear': 0.0,\n",
       "    'happiness': 1.0,\n",
       "    'neutral': 0.0,\n",
       "    'sadness': 0.0,\n",
       "    'surprise': 0.0},\n",
       "   'blur': {'blurLevel': 'low', 'value': 0.1},\n",
       "   'exposure': {'exposureLevel': 'overExposure', 'value': 0.8},\n",
       "   'noise': {'noiseLevel': 'medium', 'value': 0.64},\n",
       "   'makeup': {'eyeMakeup': True, 'lipMakeup': True},\n",
       "   'accessories': [],\n",
       "   'occlusion': {'foreheadOccluded': False,\n",
       "    'eyeOccluded': False,\n",
       "    'mouthOccluded': False},\n",
       "   'hair': {'bald': 0.02,\n",
       "    'invisible': False,\n",
       "    'hairColor': [{'color': 'brown', 'confidence': 1.0},\n",
       "     {'color': 'black', 'confidence': 0.94},\n",
       "     {'color': 'red', 'confidence': 0.18},\n",
       "     {'color': 'gray', 'confidence': 0.11},\n",
       "     {'color': 'blond', 'confidence': 0.1},\n",
       "     {'color': 'other', 'confidence': 0.07},\n",
       "     {'color': 'white', 'confidence': 0.0}]}}}]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A-2\n",
    "results = response.json()\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A-3 pandas 数据表格化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>faceId</th>\n",
       "      <th>faceRectangle.top</th>\n",
       "      <th>faceRectangle.left</th>\n",
       "      <th>faceRectangle.width</th>\n",
       "      <th>faceRectangle.height</th>\n",
       "      <th>faceAttributes.smile</th>\n",
       "      <th>faceAttributes.headPose.pitch</th>\n",
       "      <th>faceAttributes.headPose.roll</th>\n",
       "      <th>faceAttributes.headPose.yaw</th>\n",
       "      <th>faceAttributes.gender</th>\n",
       "      <th>...</th>\n",
       "      <th>faceAttributes.noise.value</th>\n",
       "      <th>faceAttributes.makeup.eyeMakeup</th>\n",
       "      <th>faceAttributes.makeup.lipMakeup</th>\n",
       "      <th>faceAttributes.accessories</th>\n",
       "      <th>faceAttributes.occlusion.foreheadOccluded</th>\n",
       "      <th>faceAttributes.occlusion.eyeOccluded</th>\n",
       "      <th>faceAttributes.occlusion.mouthOccluded</th>\n",
       "      <th>faceAttributes.hair.bald</th>\n",
       "      <th>faceAttributes.hair.invisible</th>\n",
       "      <th>faceAttributes.hair.hairColor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>670f1e49-3f7c-41f7-9f24-0530aeae0457</td>\n",
       "      <td>69</td>\n",
       "      <td>341</td>\n",
       "      <td>124</td>\n",
       "      <td>124</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>29.8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>male</td>\n",
       "      <td>...</td>\n",
       "      <td>0.64</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.02</td>\n",
       "      <td>False</td>\n",
       "      <td>[{'color': 'brown', 'confidence': 1.0}, {'colo...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 faceId  faceRectangle.top  \\\n",
       "0  670f1e49-3f7c-41f7-9f24-0530aeae0457                 69   \n",
       "\n",
       "   faceRectangle.left  faceRectangle.width  faceRectangle.height  \\\n",
       "0                 341                  124                   124   \n",
       "\n",
       "   faceAttributes.smile  faceAttributes.headPose.pitch  \\\n",
       "0                   1.0                            8.7   \n",
       "\n",
       "   faceAttributes.headPose.roll  faceAttributes.headPose.yaw  \\\n",
       "0                          29.8                          5.0   \n",
       "\n",
       "  faceAttributes.gender  ...  faceAttributes.noise.value  \\\n",
       "0                  male  ...                        0.64   \n",
       "\n",
       "   faceAttributes.makeup.eyeMakeup  faceAttributes.makeup.lipMakeup  \\\n",
       "0                             True                             True   \n",
       "\n",
       "   faceAttributes.accessories faceAttributes.occlusion.foreheadOccluded  \\\n",
       "0                          []                                     False   \n",
       "\n",
       "   faceAttributes.occlusion.eyeOccluded  \\\n",
       "0                                 False   \n",
       "\n",
       "   faceAttributes.occlusion.mouthOccluded  faceAttributes.hair.bald  \\\n",
       "0                                   False                      0.02   \n",
       "\n",
       "   faceAttributes.hair.invisible  \\\n",
       "0                          False   \n",
       "\n",
       "                       faceAttributes.hair.hairColor  \n",
       "0  [{'color': 'brown', 'confidence': 1.0}, {'colo...  \n",
       "\n",
       "[1 rows x 38 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A-3\n",
    "import pandas as pd\n",
    "df_face = pd.json_normalize(results)\n",
    "df_face"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A-4 数据取值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1f2bf379-70dd-41be-86c3-a63f2deb7c7f',\n",
       " 'f659ea05-a658-497d-9b2a-eb89e74d5403',\n",
       " '5e17a0f5-0a18-4a83-821a-31dd3fd014cd',\n",
       " 'c9b6de20-4b5c-4a87-88ce-482b2049a45c',\n",
       " 'c29e7a06-72de-4b77-bc5d-5568145f10eb',\n",
       " '0192c19c-eb0a-447b-82f1-740f32eb004a']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faceID = df_face['faceId'].values.tolist()\n",
    "faceID "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['faceId', 'faceRectangle.top', 'faceRectangle.left',\n",
       "       'faceRectangle.width', 'faceRectangle.height', 'faceAttributes.smile',\n",
       "       'faceAttributes.headPose.pitch', 'faceAttributes.headPose.roll',\n",
       "       'faceAttributes.headPose.yaw', 'faceAttributes.gender',\n",
       "       'faceAttributes.age', 'faceAttributes.facialHair.moustache',\n",
       "       'faceAttributes.facialHair.beard',\n",
       "       'faceAttributes.facialHair.sideburns', 'faceAttributes.glasses',\n",
       "       'faceAttributes.emotion.anger', 'faceAttributes.emotion.contempt',\n",
       "       'faceAttributes.emotion.disgust', 'faceAttributes.emotion.fear',\n",
       "       'faceAttributes.emotion.happiness', 'faceAttributes.emotion.neutral',\n",
       "       'faceAttributes.emotion.sadness', 'faceAttributes.emotion.surprise',\n",
       "       'faceAttributes.blur.blurLevel', 'faceAttributes.blur.value',\n",
       "       'faceAttributes.exposure.exposureLevel',\n",
       "       'faceAttributes.exposure.value', 'faceAttributes.noise.noiseLevel',\n",
       "       'faceAttributes.noise.value', 'faceAttributes.makeup.eyeMakeup',\n",
       "       'faceAttributes.makeup.lipMakeup', 'faceAttributes.accessories',\n",
       "       'faceAttributes.occlusion.foreheadOccluded',\n",
       "       'faceAttributes.occlusion.eyeOccluded',\n",
       "       'faceAttributes.occlusion.mouthOccluded', 'faceAttributes.hair.bald',\n",
       "       'faceAttributes.hair.invisible', 'faceAttributes.hair.hairColor'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检查属性/特征值\n",
    "df_face.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>faceId</th>\n",
       "      <th>faceAttributes.glasses</th>\n",
       "      <th>faceAttributes.emotion.neutral</th>\n",
       "      <th>faceAttributes.age</th>\n",
       "      <th>faceAttributes.gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1f2bf379-70dd-41be-86c3-a63f2deb7c7f</td>\n",
       "      <td>NoGlasses</td>\n",
       "      <td>0.184</td>\n",
       "      <td>19.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>f659ea05-a658-497d-9b2a-eb89e74d5403</td>\n",
       "      <td>NoGlasses</td>\n",
       "      <td>0.542</td>\n",
       "      <td>22.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5e17a0f5-0a18-4a83-821a-31dd3fd014cd</td>\n",
       "      <td>ReadingGlasses</td>\n",
       "      <td>0.000</td>\n",
       "      <td>25.0</td>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c9b6de20-4b5c-4a87-88ce-482b2049a45c</td>\n",
       "      <td>NoGlasses</td>\n",
       "      <td>0.000</td>\n",
       "      <td>23.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c29e7a06-72de-4b77-bc5d-5568145f10eb</td>\n",
       "      <td>ReadingGlasses</td>\n",
       "      <td>0.019</td>\n",
       "      <td>18.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0192c19c-eb0a-447b-82f1-740f32eb004a</td>\n",
       "      <td>NoGlasses</td>\n",
       "      <td>0.000</td>\n",
       "      <td>19.0</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 faceId faceAttributes.glasses  \\\n",
       "0  1f2bf379-70dd-41be-86c3-a63f2deb7c7f              NoGlasses   \n",
       "1  f659ea05-a658-497d-9b2a-eb89e74d5403              NoGlasses   \n",
       "2  5e17a0f5-0a18-4a83-821a-31dd3fd014cd         ReadingGlasses   \n",
       "3  c9b6de20-4b5c-4a87-88ce-482b2049a45c              NoGlasses   \n",
       "4  c29e7a06-72de-4b77-bc5d-5568145f10eb         ReadingGlasses   \n",
       "5  0192c19c-eb0a-447b-82f1-740f32eb004a              NoGlasses   \n",
       "\n",
       "   faceAttributes.emotion.neutral  faceAttributes.age faceAttributes.gender  \n",
       "0                           0.184                19.0                  male  \n",
       "1                           0.542                22.0                female  \n",
       "2                           0.000                25.0                  male  \n",
       "3                           0.000                23.0                female  \n",
       "4                           0.019                18.0                female  \n",
       "5                           0.000                19.0                female  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 可观察其中几组数据\n",
    "df_face[['faceId','faceAttributes.glasses','faceAttributes.emotion.neutral','faceAttributes.age','faceAttributes.gender']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Azure 认知服务-人脸演示"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 试一试：人脸验证(难)\n",
    "\n",
    "人脸相似度？有没有试下？\n",
    "\n",
    ">* API人脸文档中最重要的组成部分：\n",
    " >>* Request URL？\n",
    " >>* Http Method？\n",
    " >>* 参数？\n",
    "\n",
    "----\n",
    ">* 不同的人脸对比数据\n",
    "  >>* 人脸验证关键数据？\n",
    "  >>* 根据哪些数据证明是同一个人？\n",
    "    \n",
    "----\n",
    ">* 具体步骤：\n",
    "  >>* 1、Create 请求成功200 返回空字符串\n",
    "  >>* 2、Add face 请求成功200 返回persistedFaceId\n",
    "  >>* 3、Detect 准备 被检测人 人脸的id\n",
    "  >>* 4、Find similars 返回相似置信度\n",
    "  >>* 附加：get查看facelists\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://chick.cognitiveservices.azure.com/list_004 \n",
      " https://chick.cognitiveservices.azure.com/list_004 \n",
      " https://chick.cognitiveservices.azure.com/list_004\n"
     ]
    }
   ],
   "source": [
    "# 字符串拼接练习\n",
    "faceListId = \"chick\"\n",
    "# 1\n",
    "url_01 = \"https://chick.cognitiveservices.azure.com/\" + faceListId # string 拼接\n",
    "# 2\n",
    "url_02 = \"https://chick.cognitiveservices.azure.com/%s\" %(faceListId)\n",
    "# 3 \n",
    "url_03 = \"https://chick.cognitiveservices.azure.com/{}\".format(faceListId)\n",
    "print(url_01,'\\n',url_02,'\\n',url_03)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### create facelist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'{\"error\":{\"code\":\"FaceListExists\",\"message\":\"Face list \\'chick_01\\' already exists.\"}}'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import requests\n",
    "# 1、create  列表\n",
    "# faceListId\n",
    "faceListId =  \"chick_01\"#学生填写\n",
    "create_facelists_url = \"https://chick.cognitiveservices.azure.com/face/v1.0/facelists/{}\" #学生填写\n",
    "subscription_key = \"22860f2ec4fa40668703f86a97b571b6\"#学生填写\n",
    "assert subscription_key\n",
    "\n",
    "headers = {\n",
    "    # Request headers\n",
    "    'Content-Type': 'application/json',\n",
    "    'Ocp-Apim-Subscription-Key': subscription_key,\n",
    "}\n",
    "data = {\n",
    "    \"name\":\"网新周四下午课\",\n",
    "    \"userDate\":\"55人,30女,25男\",\n",
    "    \"recognitionModel\":\"recognition_03\"\n",
    "# 学生填写\n",
    "    \n",
    "}\n",
    "\n",
    "r_create = requests.put(create_facelists_url.format(faceListId), headers=headers, json=data)\n",
    "r_create.content #学生填写"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_create"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "b''"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_create.content"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### get facelist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'requests' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-2-4eba82da1d8d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# 检查你的facelist的信息\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mget_facelist_url\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"https://chick.cognitiveservices.azure.com/face/v1.0/facelists/chick_01\"\u001b[0m\u001b[1;31m# 学生填写\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mr_get_facelist\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrequests\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mget_facelist_url\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mheaders\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'requests' is not defined"
     ]
    }
   ],
   "source": [
    "# 检查你的facelist的信息\n",
    "get_facelist_url = \"https://chick.cognitiveservices.azure.com/face/v1.0/facelists/chick_01\"# 学生填写\n",
    "r_get_facelist = requests.get(get_facelist_url,headers=headers)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'persistedFaces': [], 'faceListId': 'chick_01', 'name': '网新周四下午课'}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_get_facelist.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add face 请求成功200 返回persistedFaceId\n",
    "> 我们通过上面的步骤建好了一个脸的列表，接下来我们要给这个列表添加脸了！把我们想要对比的脸存进列表吧\n",
    "- [添加人脸进列表api文档](https://docs.microsoft.com/zh-cn/rest/api/cognitiveservices/face/facelist/addfacefromurl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'subscription_key' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-96b64612d6a0>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0madd_face_url\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"https://chick.cognitiveservices.azure.com/face/v1.0/facelists/chick_01/persistedfaces\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[1;32massert\u001b[0m \u001b[0msubscription_key\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m headers = {\n\u001b[0;32m      7\u001b[0m     \u001b[1;31m# Request headers\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'subscription_key' is not defined"
     ]
    }
   ],
   "source": [
    "#先加一张脸试试\n",
    "# 2、Add face\n",
    "add_face_url = \"https://chick.cognitiveservices.azure.com/face/v1.0/facelists/chick_01/persistedfaces\"\n",
    "\n",
    "assert subscription_key\n",
    "headers = {\n",
    "    # Request headers\n",
    "    'Content-Type': 'application/json',\n",
    "    'Ocp-Apim-Subscription-Key': subscription_key,\n",
    "}\n",
    "img_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603472477147&di=6af53f0e4a6422d56f01e405ae65febd&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20180811%2Fefb2c10f038b4749b5a3669f34f26e2c.jpeg\"\n",
    "\n",
    "params_add_face={\n",
    "    \"userData\":\"jack\"\n",
    "}\n",
    "\n",
    "r_add_face = requests.post(add_face_url,headers=headers,params=params_add_face,json={\"url\":img_url})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_add_face.status_code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'persistedFaces': [{'persistedFaceId': '5d9e67fe-1efc-40c2-a47b-1fec6ed038a0',\n",
       "   'userData': 'jack'},\n",
       "  {'persistedFaceId': '2c1f2a3e-1be2-4cee-b86f-d0d2955ca12f',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': 'fcffffc5-4bb7-4861-bf2d-139f14b70ada',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': '14b1db26-575e-4779-99ee-f25572d868b7',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': '0f6c69cd-1b6f-4cdb-8c52-6632b130cb3a',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': '746d0204-6ee8-4ae0-9cf9-acf01a3c4a45',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': '15989467-2c13-4264-ad9a-462402c26d9f',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': '08eb7b73-c8f1-43a8-89a5-7fddd0bf6247',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': 'e623fda6-d2b6-4f02-a649-34cb477f6dfd',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '9e649ccf-0f9e-495d-9015-33492f4c617a',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': 'd2d389c9-fbd7-4bc8-b259-7e3f52598a2a',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': '521195a5-d1eb-4409-8153-cd626e39c5a1',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': '71d1a774-89b1-4272-913d-edd93573df6b',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': 'aebb7efd-61a2-43c2-94f3-fefa9d158ca0',\n",
       "   'userData': '黄智毅'},\n",
       "  {'persistedFaceId': '8f7c4888-4247-49c5-ad37-b05dbeeb893f',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': '2d837c33-fd3b-49b1-a6d7-94e9451118ae',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': '6ac2d219-5ffd-4e5f-aaef-33213e3f06c8',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': 'ab5c923e-0119-45a8-a21b-e127e26302f1',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': 'ec4ece7d-9934-485b-8042-335eb013832e',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': 'b90e5be6-bf70-4527-940f-38c09cd53181',\n",
       "   'userData': '张梓乐'},\n",
       "  {'persistedFaceId': '7886b65a-7ddb-4a58-8215-66453f06eb0b',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': '7a3e4931-1d82-4f60-84e7-8f5bd2be0985',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': '1288d4a0-8122-48f2-9db6-a817a2126c89',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': '87a6cc3a-8bcb-4887-bd50-f89e6e669f8a',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': '2939667f-7cb9-40dc-8ba2-d74c40eb8209',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': '5205885f-27a7-40d1-b0b7-f9657928a015',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': '32996c2b-3e32-44b0-8d87-25ae7ed88a9e',\n",
       "   'userData': '周雨'},\n",
       "  {'persistedFaceId': '2211e0e4-ceba-490b-816a-1f30a38a64a4',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': '40dc14c4-711d-4e9a-8239-5af68123f8fc',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '46bbabc7-6b15-431b-a1e8-10d94c95a839',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': 'be586d44-cdd6-438e-ae31-2f0cd3891022',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': '368bdd82-2b02-43d0-ba24-4d5f83a5d8d6',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': 'de22e58e-c15f-403a-b07e-c8945120fb0d',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': '99e90fcd-137a-4ab4-8271-80492699b4cc',\n",
       "   'userData': '黄智毅'},\n",
       "  {'persistedFaceId': 'a34f1193-302c-448b-bdbd-3609435faea7',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': '1ba88f00-00cb-4081-a2d6-ebf38024082a',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': 'b975dff7-6844-4ac0-b3d4-fc4beac11c44',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': 'd51dc9ba-f0cf-411e-8a6d-1add7f5fdf0a',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': '1ae9a43f-7ad8-475f-b8a1-9c3e92695e48',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': '771549af-94b7-4fff-965e-543f4cbfc76c',\n",
       "   'userData': '张梓乐'}],\n",
       " 'faceListId': 'chick_01',\n",
       " 'name': '网新周四下午课'}"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检查你的facelist的信息\n",
    "get_facelist_url = \"https://chick.cognitiveservices.azure.com/face/v1.0/facelists/chick_01\"\n",
    "r_get_facelist = requests.get(get_facelist_url,headers=headers)\n",
    "r_get_facelist.json()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 扩展内容，封装成函数方便多次使用 *\n",
    "> 我们要添加多张脸，但是为了减少代码量，我们可以把代码封装成函数，避免每次都要写一大堆代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 封装成函数方便添加图片/函数——可以重复使用相同的功能\n",
    "def AddFace(img_url=str,userData=str):\n",
    "    add_face_url =\"https://chick.cognitiveservices.azure.com/face/v1.0/facelists/chick_01/persistedfaces\"\n",
    "    assert subscription_key\n",
    "    headers = {\n",
    "        # Request headers\n",
    "        'Content-Type': 'application/json',\n",
    "        'Ocp-Apim-Subscription-Key': subscription_key,\n",
    "    }\n",
    "    img_url = img_url\n",
    "\n",
    "    params_add_face={\n",
    "        \"userData\":userData\n",
    "    }\n",
    "    r_add_face = requests.post(add_face_url.format(faceListId),headers=headers,params=params_add_face,json={\"url\":img_url})\n",
    "    return r_add_face.status_code#返回出状态码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/Autumnhui.jpg\",\"丘天惠\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/L-Tony-info.jpg\",\"林嘉茵\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/TLINGP.jpg\",\"汤玲萍\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/WenYanZeng.jpg\",\"曾雯燕\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/XIEIC.jpg\",\"谢依希\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/YuecongYang.png\",\"杨悦聪\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/Zoezhouyu.jpg\",\"周雨\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/crayon-heimi.jpg\",\"刘瑜鹏\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/jiayichen.jpg\",\"陈嘉仪\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/kg2000.jpg\",\"徐旖芊\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/liuxinrujiayou.jpg\",\"刘心如\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/liuyu19.png\",\"刘宇\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/ltco.jpg\",\"李婷\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/lucaszy.jpg\",\"黄智毅\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/pingzi0211.jpg\",\"黄慧文\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/shmimy-cn.jpg\",\"张铭睿\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/yichenting.jpg\",\"陈婷\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/coco022.jpg\",\"洪可凡\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/lujizhi.png\",\"卢继志\")\n",
    "AddFace(\"http://huangjieqi.gitee.io/picture_storage/zzlhyy.jpg\",\"张梓乐\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'persistedFaces': [{'persistedFaceId': '5d9e67fe-1efc-40c2-a47b-1fec6ed038a0',\n",
       "   'userData': 'jack'},\n",
       "  {'persistedFaceId': '2c1f2a3e-1be2-4cee-b86f-d0d2955ca12f',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': 'fcffffc5-4bb7-4861-bf2d-139f14b70ada',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': '14b1db26-575e-4779-99ee-f25572d868b7',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': '0f6c69cd-1b6f-4cdb-8c52-6632b130cb3a',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': '746d0204-6ee8-4ae0-9cf9-acf01a3c4a45',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': '15989467-2c13-4264-ad9a-462402c26d9f',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': '08eb7b73-c8f1-43a8-89a5-7fddd0bf6247',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': 'e623fda6-d2b6-4f02-a649-34cb477f6dfd',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '9e649ccf-0f9e-495d-9015-33492f4c617a',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': 'd2d389c9-fbd7-4bc8-b259-7e3f52598a2a',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': '521195a5-d1eb-4409-8153-cd626e39c5a1',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': '71d1a774-89b1-4272-913d-edd93573df6b',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': 'aebb7efd-61a2-43c2-94f3-fefa9d158ca0',\n",
       "   'userData': '黄智毅'},\n",
       "  {'persistedFaceId': '8f7c4888-4247-49c5-ad37-b05dbeeb893f',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': '2d837c33-fd3b-49b1-a6d7-94e9451118ae',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': '6ac2d219-5ffd-4e5f-aaef-33213e3f06c8',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': 'ab5c923e-0119-45a8-a21b-e127e26302f1',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': 'ec4ece7d-9934-485b-8042-335eb013832e',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': 'b90e5be6-bf70-4527-940f-38c09cd53181',\n",
       "   'userData': '张梓乐'},\n",
       "  {'persistedFaceId': '7886b65a-7ddb-4a58-8215-66453f06eb0b',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': '7a3e4931-1d82-4f60-84e7-8f5bd2be0985',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': '1288d4a0-8122-48f2-9db6-a817a2126c89',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': '87a6cc3a-8bcb-4887-bd50-f89e6e669f8a',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': '2939667f-7cb9-40dc-8ba2-d74c40eb8209',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': '5205885f-27a7-40d1-b0b7-f9657928a015',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': '32996c2b-3e32-44b0-8d87-25ae7ed88a9e',\n",
       "   'userData': '周雨'},\n",
       "  {'persistedFaceId': '2211e0e4-ceba-490b-816a-1f30a38a64a4',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': '40dc14c4-711d-4e9a-8239-5af68123f8fc',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '46bbabc7-6b15-431b-a1e8-10d94c95a839',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': 'be586d44-cdd6-438e-ae31-2f0cd3891022',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': '368bdd82-2b02-43d0-ba24-4d5f83a5d8d6',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': 'de22e58e-c15f-403a-b07e-c8945120fb0d',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': '99e90fcd-137a-4ab4-8271-80492699b4cc',\n",
       "   'userData': '黄智毅'},\n",
       "  {'persistedFaceId': 'a34f1193-302c-448b-bdbd-3609435faea7',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': '1ba88f00-00cb-4081-a2d6-ebf38024082a',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': 'b975dff7-6844-4ac0-b3d4-fc4beac11c44',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': 'd51dc9ba-f0cf-411e-8a6d-1add7f5fdf0a',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': '1ae9a43f-7ad8-475f-b8a1-9c3e92695e48',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': '771549af-94b7-4fff-965e-543f4cbfc76c',\n",
       "   'userData': '张梓乐'},\n",
       "  {'persistedFaceId': '4352477f-9f9a-4b2c-b06e-a1ca97b86884',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': '4a15a5df-2665-40b5-99ce-8b40be80091a',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': 'ce5e84b5-0247-4f68-9957-98a955c61748',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': '7419099f-fa36-4081-adbc-4c8131a728bc',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': '1cebd4b4-ba21-4ef9-8b82-0dd3592967ef',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': '1751a091-715e-4995-ab92-c0c512c3c747',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': '8c13e84c-76fd-4ae8-ab3e-3e5adf43982f',\n",
       "   'userData': '周雨'},\n",
       "  {'persistedFaceId': '39f3c5ac-f138-4c91-8793-021cacaf236b',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': 'cfd74e07-9923-4cc6-a50a-104141389948',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '2421d1ce-0cb7-4a63-ba8b-abe39722bed0',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': 'a97e2540-6b69-42eb-9428-45f2d041b9de',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': 'fa9efbff-3fbb-49f0-ae48-3ec667a3897f',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': '84c4aa5b-8ab0-4494-91df-d117042c6801',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': '953d2517-1981-4d9e-b198-a5c32a0b79dc',\n",
       "   'userData': '黄智毅'},\n",
       "  {'persistedFaceId': 'bb26eb5f-d324-4463-9f96-837f83dd908b',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': 'f77bd3d8-9342-40e5-817f-0bd2c0af4564',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': '5dcfa143-a5e9-4250-8057-d39d7f05067f',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': '64996f16-a714-4e51-ab73-efe1974f46a8',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': '08732847-7311-4a2f-b2a7-ef87d49582d5',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': 'a49e624a-645b-4f81-b236-bbf1767c91ec',\n",
       "   'userData': '张梓乐'},\n",
       "  {'persistedFaceId': '68dca36b-255a-413e-a6b3-bc0f6afd4a6e',\n",
       "   'userData': 'jack'},\n",
       "  {'persistedFaceId': 'bb073d0b-1a72-46a9-8117-b7dd97aa87b9',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': '46fe9caa-986b-488c-aa3d-dca7c51ad6b6',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': 'f7e14b14-7efe-485b-80de-5cb4ccbb9f7e',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': 'a4b49373-3d60-4603-8ad8-04f948f4db98',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': 'd885941c-cf1d-451a-a802-a4e1c208701e',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': 'eca1ab76-9544-4c80-b50f-bc7d5001da96',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': '06816e52-553c-4f49-b978-5dcf368f401c',\n",
       "   'userData': '周雨'},\n",
       "  {'persistedFaceId': 'cfd7b25d-783a-460c-84b8-ddd7705ae709',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': 'fe8c2951-091a-41e8-b144-0cec35515a7b',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '41684a27-add4-45e8-b791-5d417faba1e8',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': 'e0ccfcac-f66d-4f2c-99f5-d0b8159fd02c',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': '8a80671c-014c-40dd-ac9b-4f0a9ce0040d',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': 'e458b251-564b-4c24-8cd3-7f31cd85c82e',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': 'd1e3ded5-6ade-4a0a-a260-33d88aa82861',\n",
       "   'userData': '黄智毅'},\n",
       "  {'persistedFaceId': '257958f7-f3c8-4217-990c-4cef3e617ead',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': 'cc8ec348-417f-4e16-a90d-bbb8aabe3440',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': '2371eea9-22c0-41e8-8e98-be2b769c9cc0',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': 'e4cd5987-8ba0-4a86-9cc4-36918ad8d4d4',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': '2f00b07a-41d5-47c6-83c0-30b6eb92b39c',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': 'b7907f37-3b9b-4cbb-813e-b4358cd11fa1',\n",
       "   'userData': '张梓乐'}],\n",
       " 'faceListId': 'chick_01',\n",
       " 'name': '网新周四下午课'}"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检查你的facelist的信息\n",
    "get_facelist_url = \"https://chick.cognitiveservices.azure.com/face/v1.0/facelists/chick_01\"\n",
    "r_get_facelist = requests.get(get_facelist_url,headers=headers)\n",
    "r_get_facelist.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'4a15a5df-2665-40b5-99ce-8b40be80091a'"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 键/值\n",
    "for i in faceId:\n",
    "#     print(i)\n",
    "    if i[\"userData\"] == \"林嘉茵\":\n",
    "        faceId_02 = i['persistedFaceId']\n",
    "faceId_02\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'persistedFaceId': '5d9e67fe-1efc-40c2-a47b-1fec6ed038a0',\n",
       "  'userData': 'jack'},\n",
       " {'persistedFaceId': '2c1f2a3e-1be2-4cee-b86f-d0d2955ca12f',\n",
       "  'userData': '丘天惠'},\n",
       " {'persistedFaceId': 'fcffffc5-4bb7-4861-bf2d-139f14b70ada',\n",
       "  'userData': '林嘉茵'},\n",
       " {'persistedFaceId': '14b1db26-575e-4779-99ee-f25572d868b7',\n",
       "  'userData': '汤玲萍'},\n",
       " {'persistedFaceId': '0f6c69cd-1b6f-4cdb-8c52-6632b130cb3a',\n",
       "  'userData': '曾雯燕'},\n",
       " {'persistedFaceId': '746d0204-6ee8-4ae0-9cf9-acf01a3c4a45',\n",
       "  'userData': '谢依希'},\n",
       " {'persistedFaceId': '15989467-2c13-4264-ad9a-462402c26d9f',\n",
       "  'userData': '杨悦聪'},\n",
       " {'persistedFaceId': '08eb7b73-c8f1-43a8-89a5-7fddd0bf6247',\n",
       "  'userData': '刘瑜鹏'},\n",
       " {'persistedFaceId': 'e623fda6-d2b6-4f02-a649-34cb477f6dfd',\n",
       "  'userData': '陈嘉仪'},\n",
       " {'persistedFaceId': '9e649ccf-0f9e-495d-9015-33492f4c617a',\n",
       "  'userData': '徐旖芊'},\n",
       " {'persistedFaceId': 'd2d389c9-fbd7-4bc8-b259-7e3f52598a2a',\n",
       "  'userData': '刘心如'},\n",
       " {'persistedFaceId': '521195a5-d1eb-4409-8153-cd626e39c5a1', 'userData': '刘宇'},\n",
       " {'persistedFaceId': '71d1a774-89b1-4272-913d-edd93573df6b', 'userData': '李婷'},\n",
       " {'persistedFaceId': 'aebb7efd-61a2-43c2-94f3-fefa9d158ca0',\n",
       "  'userData': '黄智毅'},\n",
       " {'persistedFaceId': '8f7c4888-4247-49c5-ad37-b05dbeeb893f',\n",
       "  'userData': '黄慧文'},\n",
       " {'persistedFaceId': '2d837c33-fd3b-49b1-a6d7-94e9451118ae',\n",
       "  'userData': '张铭睿'},\n",
       " {'persistedFaceId': '6ac2d219-5ffd-4e5f-aaef-33213e3f06c8', 'userData': '陈婷'},\n",
       " {'persistedFaceId': 'ab5c923e-0119-45a8-a21b-e127e26302f1',\n",
       "  'userData': '洪可凡'},\n",
       " {'persistedFaceId': 'ec4ece7d-9934-485b-8042-335eb013832e',\n",
       "  'userData': '卢继志'},\n",
       " {'persistedFaceId': 'b90e5be6-bf70-4527-940f-38c09cd53181',\n",
       "  'userData': '张梓乐'},\n",
       " {'persistedFaceId': '7886b65a-7ddb-4a58-8215-66453f06eb0b',\n",
       "  'userData': '丘天惠'},\n",
       " {'persistedFaceId': '7a3e4931-1d82-4f60-84e7-8f5bd2be0985',\n",
       "  'userData': '林嘉茵'},\n",
       " {'persistedFaceId': '1288d4a0-8122-48f2-9db6-a817a2126c89',\n",
       "  'userData': '汤玲萍'},\n",
       " {'persistedFaceId': '87a6cc3a-8bcb-4887-bd50-f89e6e669f8a',\n",
       "  'userData': '曾雯燕'},\n",
       " {'persistedFaceId': '2939667f-7cb9-40dc-8ba2-d74c40eb8209',\n",
       "  'userData': '谢依希'},\n",
       " {'persistedFaceId': '5205885f-27a7-40d1-b0b7-f9657928a015',\n",
       "  'userData': '杨悦聪'},\n",
       " {'persistedFaceId': '32996c2b-3e32-44b0-8d87-25ae7ed88a9e', 'userData': '周雨'},\n",
       " {'persistedFaceId': '2211e0e4-ceba-490b-816a-1f30a38a64a4',\n",
       "  'userData': '刘瑜鹏'},\n",
       " {'persistedFaceId': '40dc14c4-711d-4e9a-8239-5af68123f8fc',\n",
       "  'userData': '陈嘉仪'},\n",
       " {'persistedFaceId': '46bbabc7-6b15-431b-a1e8-10d94c95a839',\n",
       "  'userData': '徐旖芊'},\n",
       " {'persistedFaceId': 'be586d44-cdd6-438e-ae31-2f0cd3891022',\n",
       "  'userData': '刘心如'},\n",
       " {'persistedFaceId': '368bdd82-2b02-43d0-ba24-4d5f83a5d8d6', 'userData': '刘宇'},\n",
       " {'persistedFaceId': 'de22e58e-c15f-403a-b07e-c8945120fb0d', 'userData': '李婷'},\n",
       " {'persistedFaceId': '99e90fcd-137a-4ab4-8271-80492699b4cc',\n",
       "  'userData': '黄智毅'},\n",
       " {'persistedFaceId': 'a34f1193-302c-448b-bdbd-3609435faea7',\n",
       "  'userData': '黄慧文'},\n",
       " {'persistedFaceId': '1ba88f00-00cb-4081-a2d6-ebf38024082a',\n",
       "  'userData': '张铭睿'},\n",
       " {'persistedFaceId': 'b975dff7-6844-4ac0-b3d4-fc4beac11c44', 'userData': '陈婷'},\n",
       " {'persistedFaceId': 'd51dc9ba-f0cf-411e-8a6d-1add7f5fdf0a',\n",
       "  'userData': '洪可凡'},\n",
       " {'persistedFaceId': '1ae9a43f-7ad8-475f-b8a1-9c3e92695e48',\n",
       "  'userData': '卢继志'},\n",
       " {'persistedFaceId': '771549af-94b7-4fff-965e-543f4cbfc76c',\n",
       "  'userData': '张梓乐'},\n",
       " {'persistedFaceId': '4352477f-9f9a-4b2c-b06e-a1ca97b86884',\n",
       "  'userData': '丘天惠'},\n",
       " {'persistedFaceId': '4a15a5df-2665-40b5-99ce-8b40be80091a',\n",
       "  'userData': '林嘉茵'},\n",
       " {'persistedFaceId': 'ce5e84b5-0247-4f68-9957-98a955c61748',\n",
       "  'userData': '汤玲萍'},\n",
       " {'persistedFaceId': '7419099f-fa36-4081-adbc-4c8131a728bc',\n",
       "  'userData': '曾雯燕'},\n",
       " {'persistedFaceId': '1cebd4b4-ba21-4ef9-8b82-0dd3592967ef',\n",
       "  'userData': '谢依希'},\n",
       " {'persistedFaceId': '1751a091-715e-4995-ab92-c0c512c3c747',\n",
       "  'userData': '杨悦聪'},\n",
       " {'persistedFaceId': '8c13e84c-76fd-4ae8-ab3e-3e5adf43982f', 'userData': '周雨'},\n",
       " {'persistedFaceId': '39f3c5ac-f138-4c91-8793-021cacaf236b',\n",
       "  'userData': '刘瑜鹏'},\n",
       " {'persistedFaceId': 'cfd74e07-9923-4cc6-a50a-104141389948',\n",
       "  'userData': '陈嘉仪'},\n",
       " {'persistedFaceId': '2421d1ce-0cb7-4a63-ba8b-abe39722bed0',\n",
       "  'userData': '徐旖芊'},\n",
       " {'persistedFaceId': 'a97e2540-6b69-42eb-9428-45f2d041b9de',\n",
       "  'userData': '刘心如'},\n",
       " {'persistedFaceId': 'fa9efbff-3fbb-49f0-ae48-3ec667a3897f', 'userData': '刘宇'},\n",
       " {'persistedFaceId': '84c4aa5b-8ab0-4494-91df-d117042c6801', 'userData': '李婷'},\n",
       " {'persistedFaceId': '953d2517-1981-4d9e-b198-a5c32a0b79dc',\n",
       "  'userData': '黄智毅'},\n",
       " {'persistedFaceId': 'bb26eb5f-d324-4463-9f96-837f83dd908b',\n",
       "  'userData': '黄慧文'},\n",
       " {'persistedFaceId': 'f77bd3d8-9342-40e5-817f-0bd2c0af4564',\n",
       "  'userData': '张铭睿'},\n",
       " {'persistedFaceId': '5dcfa143-a5e9-4250-8057-d39d7f05067f', 'userData': '陈婷'},\n",
       " {'persistedFaceId': '64996f16-a714-4e51-ab73-efe1974f46a8',\n",
       "  'userData': '洪可凡'},\n",
       " {'persistedFaceId': '08732847-7311-4a2f-b2a7-ef87d49582d5',\n",
       "  'userData': '卢继志'},\n",
       " {'persistedFaceId': 'a49e624a-645b-4f81-b236-bbf1767c91ec',\n",
       "  'userData': '张梓乐'},\n",
       " {'persistedFaceId': '68dca36b-255a-413e-a6b3-bc0f6afd4a6e',\n",
       "  'userData': 'jack'},\n",
       " {'persistedFaceId': 'bb073d0b-1a72-46a9-8117-b7dd97aa87b9',\n",
       "  'userData': '丘天惠'},\n",
       " {'persistedFaceId': '46fe9caa-986b-488c-aa3d-dca7c51ad6b6',\n",
       "  'userData': '林嘉茵'},\n",
       " {'persistedFaceId': 'f7e14b14-7efe-485b-80de-5cb4ccbb9f7e',\n",
       "  'userData': '汤玲萍'},\n",
       " {'persistedFaceId': 'a4b49373-3d60-4603-8ad8-04f948f4db98',\n",
       "  'userData': '曾雯燕'},\n",
       " {'persistedFaceId': 'd885941c-cf1d-451a-a802-a4e1c208701e',\n",
       "  'userData': '谢依希'},\n",
       " {'persistedFaceId': 'eca1ab76-9544-4c80-b50f-bc7d5001da96',\n",
       "  'userData': '杨悦聪'},\n",
       " {'persistedFaceId': '06816e52-553c-4f49-b978-5dcf368f401c', 'userData': '周雨'},\n",
       " {'persistedFaceId': 'cfd7b25d-783a-460c-84b8-ddd7705ae709',\n",
       "  'userData': '刘瑜鹏'},\n",
       " {'persistedFaceId': 'fe8c2951-091a-41e8-b144-0cec35515a7b',\n",
       "  'userData': '陈嘉仪'},\n",
       " {'persistedFaceId': '41684a27-add4-45e8-b791-5d417faba1e8',\n",
       "  'userData': '徐旖芊'},\n",
       " {'persistedFaceId': 'e0ccfcac-f66d-4f2c-99f5-d0b8159fd02c',\n",
       "  'userData': '刘心如'},\n",
       " {'persistedFaceId': '8a80671c-014c-40dd-ac9b-4f0a9ce0040d', 'userData': '刘宇'},\n",
       " {'persistedFaceId': 'e458b251-564b-4c24-8cd3-7f31cd85c82e', 'userData': '李婷'},\n",
       " {'persistedFaceId': 'd1e3ded5-6ade-4a0a-a260-33d88aa82861',\n",
       "  'userData': '黄智毅'},\n",
       " {'persistedFaceId': '257958f7-f3c8-4217-990c-4cef3e617ead',\n",
       "  'userData': '黄慧文'},\n",
       " {'persistedFaceId': 'cc8ec348-417f-4e16-a90d-bbb8aabe3440',\n",
       "  'userData': '张铭睿'},\n",
       " {'persistedFaceId': '2371eea9-22c0-41e8-8e98-be2b769c9cc0', 'userData': '陈婷'},\n",
       " {'persistedFaceId': 'e4cd5987-8ba0-4a86-9cc4-36918ad8d4d4',\n",
       "  'userData': '洪可凡'},\n",
       " {'persistedFaceId': '2f00b07a-41d5-47c6-83c0-30b6eb92b39c',\n",
       "  'userData': '卢继志'},\n",
       " {'persistedFaceId': 'b7907f37-3b9b-4cbb-813e-b4358cd11fa1',\n",
       "  'userData': '张梓乐'}]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "faceId =  r_get_facelist.json()['persistedFaces']\n",
    "faceId"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "aebb7efd-61a2-43c2-94f3-fefa9d158ca0\n",
      "99e90fcd-137a-4ab4-8271-80492699b4cc\n",
      "953d2517-1981-4d9e-b198-a5c32a0b79dc\n",
      "d1e3ded5-6ade-4a0a-a260-33d88aa82861\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'d1e3ded5-6ade-4a0a-a260-33d88aa82861'"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for item in faceId:\n",
    "#     print(item)\n",
    "    if item['userData'] == '黄智毅':\n",
    "        print(item['persistedFaceId'])\n",
    "        delate_face = item['persistedFaceId']\n",
    "delate_face"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### delate face"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Detect face 删除列表内人脸id\n",
    "faceListId = \n",
    "delete_face_url =\n",
    "\n",
    "assert subscription_key\n",
    "# 例如：删除黄志毅： {'persistedFaceId': '69103b48-b6c4-4f58-8ac1-4c8b84e56bc1','userData': '黄智毅'},\n",
    "\n",
    "\n",
    "persistedFaceId = delate_face\n",
    "# 直接取上面获得的ID{'persistedFaceId': 'f18450d3-60d2-45f3-a69e-783574dc3ce8'} \n",
    "\n",
    "headers = {\n",
    "    # Request headers\n",
    "    'Content-Type': 'application/json',\n",
    "    'Ocp-Apim-Subscription-Key': subscription_key,\n",
    "}\n",
    "\n",
    "# 注意requests请求为delete\n",
    "r_delete_face = requests.delete(delete_face_url.format(faceListId,persistedFaceId),headers=headers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_delete_face"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'persistedFaces': [{'persistedFaceId': 'dbb1ee2f-7a47-4533-b1f4-b04ff25b3aa4',\n",
       "   'userData': '丘某峰'},\n",
       "  {'persistedFaceId': '057aed14-1033-4e52-b340-6d44c8e0b698',\n",
       "   'userData': '丘天惠'},\n",
       "  {'persistedFaceId': '2841fe7a-067b-4b3b-9f9f-8573bf03738f',\n",
       "   'userData': '林嘉茵'},\n",
       "  {'persistedFaceId': '8c489b85-4101-4239-a16e-910ecc93e4ca',\n",
       "   'userData': '汤玲萍'},\n",
       "  {'persistedFaceId': '7eed72ad-ad8c-49b0-9e3c-1e2f19c1f82e',\n",
       "   'userData': '曾雯燕'},\n",
       "  {'persistedFaceId': '7bcddf93-1bcc-4734-a87b-73d2b3e17b2b',\n",
       "   'userData': '谢依希'},\n",
       "  {'persistedFaceId': 'a0ba6f50-699d-4b0e-b12b-78664b90e4e3',\n",
       "   'userData': '杨悦聪'},\n",
       "  {'persistedFaceId': '23a4d101-69c3-4d31-9a03-bf7a85f9aad7',\n",
       "   'userData': '周雨'},\n",
       "  {'persistedFaceId': '5138f36e-0cf5-45c2-bd64-13573d65a118',\n",
       "   'userData': '刘瑜鹏'},\n",
       "  {'persistedFaceId': '033b5448-8c13-4e8d-b2df-0106088e181b',\n",
       "   'userData': '陈嘉仪'},\n",
       "  {'persistedFaceId': '819f9bf8-4efe-4374-ae23-bf0928514fcd',\n",
       "   'userData': '徐旖芊'},\n",
       "  {'persistedFaceId': '64289df3-2ea4-4beb-a638-9e2088b11d1a',\n",
       "   'userData': '刘心如'},\n",
       "  {'persistedFaceId': '2d73d2bb-42b9-4bfd-97cd-a26db504f41e',\n",
       "   'userData': '刘宇'},\n",
       "  {'persistedFaceId': 'cb7c10b6-699f-4940-885b-f01e8ed47e8a',\n",
       "   'userData': '李婷'},\n",
       "  {'persistedFaceId': 'cb430228-620e-4283-96ee-8df1bbd78e0f',\n",
       "   'userData': '黄慧文'},\n",
       "  {'persistedFaceId': '68c38ba1-ed3e-4bd5-9229-f10206bc111e',\n",
       "   'userData': '张铭睿'},\n",
       "  {'persistedFaceId': '711aaa90-acf0-422b-be1e-ee6ad49cd076',\n",
       "   'userData': '陈婷'},\n",
       "  {'persistedFaceId': '7114e51d-b25f-48ad-bf3f-cfc81a0c32c1',\n",
       "   'userData': '洪可凡'},\n",
       "  {'persistedFaceId': '9791b51b-b1db-4cc5-8074-c0cac4563c83',\n",
       "   'userData': '卢继志'},\n",
       "  {'persistedFaceId': 'a7eb090e-38ee-4f93-9cad-beff1f95ca0f',\n",
       "   'userData': '张梓乐'}],\n",
       " 'faceListId': 'zhichao06',\n",
       " 'name': 'api_facelist',\n",
       " 'userData': '相册集'}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检查你的facelist的信息\n",
    "get_facelist_url =\n",
    "r_get_facelist = requests.get(get_facelist_url,headers=headers)\n",
    "r_get_facelist.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Find similars 返回相似置信度\n",
    "- [监测人脸相似度api文档](https://docs.microsoft.com/zh-cn/rest/api/cognitiveservices/face/face/findsimilar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'faceId': '65109723-281a-4e9b-abfd-6ade9722bda7',\n",
       "  'faceRectangle': {'top': 75, 'left': 75, 'width': 133, 'height': 133}}]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Detect 检测人脸的id\n",
    "# replace <My Endpoint String> with the string from your endpoint URL\n",
    "face_api_url = 'https://chick.cognitiveservices.azure.com/face/v1.0/detect'\n",
    "\n",
    "# 请求正文\n",
    "image_url = 'https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603472477147&di=6af53f0e4a6422d56f01e405ae65febd&imgtype=0&src=http%3A%2F%2F5b0988e595225.cdn.sohucs.com%2Fimages%2F20180811%2Fefb2c10f038b4749b5a3669f34f26e2c.jpeg'\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': subscription_key}\n",
    "\n",
    "# 请求参数\n",
    "params = {\n",
    "    'returnFaceId': 'true',\n",
    "    'returnFaceLandmarks': 'false',\n",
    "    # 选择model\n",
    "    'recognitionModel':'recognition_03',#此参数需与facelist参数一致\n",
    "    'detectionModel':'detection_01',\n",
    "    # 可选参数,请仔细阅读API文档\n",
    "    'returnFaceAttributes': '',\n",
    "}\n",
    "\n",
    "response = requests.post(face_api_url, params=params,\n",
    "                         headers=headers, json={\"url\": image_url})\n",
    "# json.dumps 将json--->字符串\n",
    "response.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "findsimilars_url = \"https://chick.cognitiveservices.azure.com/face/v1.0/findsimilars\"\n",
    "\n",
    "# 请求正文 faceId需要先检测一张照片获取\n",
    "data_findsimilars = {\n",
    "    \"faceId\":\"65109723-281a-4e9b-abfd-6ade9722bda7\",#取上方的faceID\n",
    "    \"faceListId\": \"chick_01\",\n",
    "#     \"faceIds\":faceId_02,\n",
    "    \"maxNumOfCandidatesReturned\": 10,\n",
    "    \"mode\": \"matchFace\"#matchPerson #一种为验证模式，一种为相似值模式\n",
    "    }\n",
    "\n",
    "r_findsimilars = requests.post(findsimilars_url,headers=headers,json=data_findsimilars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_findsimilars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'persistedFaceId': '5d9e67fe-1efc-40c2-a47b-1fec6ed038a0',\n",
       "  'confidence': 1.0},\n",
       " {'persistedFaceId': '68dca36b-255a-413e-a6b3-bc0f6afd4a6e',\n",
       "  'confidence': 1.0},\n",
       " {'persistedFaceId': '14b1db26-575e-4779-99ee-f25572d868b7',\n",
       "  'confidence': 0.09491},\n",
       " {'persistedFaceId': '1288d4a0-8122-48f2-9db6-a817a2126c89',\n",
       "  'confidence': 0.09491},\n",
       " {'persistedFaceId': 'ce5e84b5-0247-4f68-9957-98a955c61748',\n",
       "  'confidence': 0.09491},\n",
       " {'persistedFaceId': 'f7e14b14-7efe-485b-80de-5cb4ccbb9f7e',\n",
       "  'confidence': 0.09491},\n",
       " {'persistedFaceId': '9e649ccf-0f9e-495d-9015-33492f4c617a',\n",
       "  'confidence': 0.09488},\n",
       " {'persistedFaceId': '46bbabc7-6b15-431b-a1e8-10d94c95a839',\n",
       "  'confidence': 0.09488},\n",
       " {'persistedFaceId': '2421d1ce-0cb7-4a63-ba8b-abe39722bed0',\n",
       "  'confidence': 0.09488},\n",
       " {'persistedFaceId': '41684a27-add4-45e8-b791-5d417faba1e8',\n",
       "  'confidence': 0.09488}]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_findsimilars.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>persistedFaceId</th>\n",
       "      <th>userData</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5d9e67fe-1efc-40c2-a47b-1fec6ed038a0</td>\n",
       "      <td>jack</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2c1f2a3e-1be2-4cee-b86f-d0d2955ca12f</td>\n",
       "      <td>丘天惠</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fcffffc5-4bb7-4861-bf2d-139f14b70ada</td>\n",
       "      <td>林嘉茵</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14b1db26-575e-4779-99ee-f25572d868b7</td>\n",
       "      <td>汤玲萍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0f6c69cd-1b6f-4cdb-8c52-6632b130cb3a</td>\n",
       "      <td>曾雯燕</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>cc8ec348-417f-4e16-a90d-bbb8aabe3440</td>\n",
       "      <td>张铭睿</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2371eea9-22c0-41e8-8e98-be2b769c9cc0</td>\n",
       "      <td>陈婷</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>e4cd5987-8ba0-4a86-9cc4-36918ad8d4d4</td>\n",
       "      <td>洪可凡</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2f00b07a-41d5-47c6-83c0-30b6eb92b39c</td>\n",
       "      <td>卢继志</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>b7907f37-3b9b-4cbb-813e-b4358cd11fa1</td>\n",
       "      <td>张梓乐</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         persistedFaceId userData\n",
       "0   5d9e67fe-1efc-40c2-a47b-1fec6ed038a0     jack\n",
       "1   2c1f2a3e-1be2-4cee-b86f-d0d2955ca12f      丘天惠\n",
       "2   fcffffc5-4bb7-4861-bf2d-139f14b70ada      林嘉茵\n",
       "3   14b1db26-575e-4779-99ee-f25572d868b7      汤玲萍\n",
       "4   0f6c69cd-1b6f-4cdb-8c52-6632b130cb3a      曾雯燕\n",
       "..                                   ...      ...\n",
       "76  cc8ec348-417f-4e16-a90d-bbb8aabe3440      张铭睿\n",
       "77  2371eea9-22c0-41e8-8e98-be2b769c9cc0       陈婷\n",
       "78  e4cd5987-8ba0-4a86-9cc4-36918ad8d4d4      洪可凡\n",
       "79  2f00b07a-41d5-47c6-83c0-30b6eb92b39c      卢继志\n",
       "80  b7907f37-3b9b-4cbb-813e-b4358cd11fa1      张梓乐\n",
       "\n",
       "[81 rows x 2 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "#facelist里面的数据\n",
    "faceListId_df = pd.json_normalize(r_get_facelist.json()[\"persistedFaces\"])# 升级pandas才能运行\n",
    "faceListId_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>persistedFaceId</th>\n",
       "      <th>confidence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4278a690-5f78-40d7-abe5-88eab5d5494f</td>\n",
       "      <td>0.29269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8b1c2538-05cc-4636-8460-cfa8059d5c72</td>\n",
       "      <td>0.20908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5bfad450-0274-40b5-ba9f-0e4a0af9763b</td>\n",
       "      <td>0.17849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1</td>\n",
       "      <td>0.16209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e61d920f-f131-464a-9a43-a82babf20358</td>\n",
       "      <td>0.15023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6a663a8e-725c-4c7d-bd72-5520c4a2e93e</td>\n",
       "      <td>0.10100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>8a559e64-a44b-4a4b-84dc-e14da959da3a</td>\n",
       "      <td>0.10034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0523267b-6750-4d1e-987d-674e0ecb0821</td>\n",
       "      <td>0.09990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5081698a-efe4-4be9-822c-cb58f2cc4803</td>\n",
       "      <td>0.09955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>d0c25191-8224-410e-9eed-df3457e0a77f</td>\n",
       "      <td>0.09503</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        persistedFaceId  confidence\n",
       "0  4278a690-5f78-40d7-abe5-88eab5d5494f     0.29269\n",
       "1  8b1c2538-05cc-4636-8460-cfa8059d5c72     0.20908\n",
       "2  5bfad450-0274-40b5-ba9f-0e4a0af9763b     0.17849\n",
       "3  c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1     0.16209\n",
       "4  e61d920f-f131-464a-9a43-a82babf20358     0.15023\n",
       "5  6a663a8e-725c-4c7d-bd72-5520c4a2e93e     0.10100\n",
       "6  8a559e64-a44b-4a4b-84dc-e14da959da3a     0.10034\n",
       "7  0523267b-6750-4d1e-987d-674e0ecb0821     0.09990\n",
       "8  5081698a-efe4-4be9-822c-cb58f2cc4803     0.09955\n",
       "9  d0c25191-8224-410e-9eed-df3457e0a77f     0.09503"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 返回相似度的数据\n",
    "find_df = pd.json_normalize(r_findsimilars.json())# 升级pandas才能运行\n",
    "find_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>persistedFaceId</th>\n",
       "      <th>userData</th>\n",
       "      <th>confidence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4278a690-5f78-40d7-abe5-88eab5d5494f</td>\n",
       "      <td>徐旖芊</td>\n",
       "      <td>0.29269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8b1c2538-05cc-4636-8460-cfa8059d5c72</td>\n",
       "      <td>李婷</td>\n",
       "      <td>0.20908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5bfad450-0274-40b5-ba9f-0e4a0af9763b</td>\n",
       "      <td>张铭睿</td>\n",
       "      <td>0.17849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1</td>\n",
       "      <td>陈嘉仪</td>\n",
       "      <td>0.16209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e61d920f-f131-464a-9a43-a82babf20358</td>\n",
       "      <td>刘心如</td>\n",
       "      <td>0.15023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>6a663a8e-725c-4c7d-bd72-5520c4a2e93e</td>\n",
       "      <td>洪可凡</td>\n",
       "      <td>0.10100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8a559e64-a44b-4a4b-84dc-e14da959da3a</td>\n",
       "      <td>林嘉茵</td>\n",
       "      <td>0.10034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0523267b-6750-4d1e-987d-674e0ecb0821</td>\n",
       "      <td>张梓乐</td>\n",
       "      <td>0.09990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5081698a-efe4-4be9-822c-cb58f2cc4803</td>\n",
       "      <td>丘某峰</td>\n",
       "      <td>0.09955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>d0c25191-8224-410e-9eed-df3457e0a77f</td>\n",
       "      <td>黄智毅</td>\n",
       "      <td>0.09503</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        persistedFaceId userData  confidence\n",
       "3  4278a690-5f78-40d7-abe5-88eab5d5494f      徐旖芊     0.29269\n",
       "5  8b1c2538-05cc-4636-8460-cfa8059d5c72       李婷     0.20908\n",
       "7  5bfad450-0274-40b5-ba9f-0e4a0af9763b      张铭睿     0.17849\n",
       "2  c0ee4410-bca0-4a3f-acb5-74c8eb72f0a1      陈嘉仪     0.16209\n",
       "4  e61d920f-f131-464a-9a43-a82babf20358      刘心如     0.15023\n",
       "8  6a663a8e-725c-4c7d-bd72-5520c4a2e93e      洪可凡     0.10100\n",
       "1  8a559e64-a44b-4a4b-84dc-e14da959da3a      林嘉茵     0.10034\n",
       "9  0523267b-6750-4d1e-987d-674e0ecb0821      张梓乐     0.09990\n",
       "0  5081698a-efe4-4be9-822c-cb58f2cc4803      丘某峰     0.09955\n",
       "6  d0c25191-8224-410e-9eed-df3457e0a77f      黄智毅     0.09503"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(faceListId_df, find_df,how='inner', on='persistedFaceId').sort_values(by=\"confidence\",ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 设计人脸识别门禁/打卡/签到 小程序"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Face++ FaceSets 实践\n",
    "\n",
    "\n",
    ">* 1. FaceSet Create\n",
    ">* 2. FaceSet GetDetail\n",
    ">* 3. FaceSet AddFace\n",
    ">* 4. FaceSet RemoveFace\n",
    ">* 5. FaceSet Update\n",
    ">* 6. Compare Face"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 准备工作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "api_secret = \"cCgd0W4aKtbCdxQYy9DuxTcs1DwFPtk9\"\n",
    "api_key = '3hc0EXssRUfkJGEnnBBQPrzBVHcQaPyp'  # Replace with a valid Subscription Key here."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet Create（创建人脸集合）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. FaceSet Create\n",
    "import requests,json\n",
    "\n",
    "display_name = \"网新二班人脸集合\"\n",
    "outer_id = \"00001\"\n",
    "user_data = \"52人，20男生，32女生\"\n",
    "\n",
    "CreateFace_Url = \"https://api-cn.faceplusplus.com/facepp/v3/faceset/create\"\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'display_name':display_name,\n",
    "    'outer_id':outer_id,\n",
    "    'user_data':user_data\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(CreateFace_Url, params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'time_used': 180,\n",
       " 'error_message': 'FACESET_EXIST',\n",
       " 'request_id': '1603431469,b281a99e-6f78-4978-94e1-962494477961'}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet GetDetail（获取人脸集合信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "GetDetail_Url = \"https://api-cn.faceplusplus.com/facepp/v3/faceset/getdetail\"\n",
    "\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'outer_id':outer_id,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(GetDetail_Url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'faceset_token': '8ae27be5f5b6487cad35babfd759dfd3',\n",
       " 'tags': '',\n",
       " 'time_used': 114,\n",
       " 'user_data': '52人，20男生，32女生',\n",
       " 'display_name': '网新二班人脸集合',\n",
       " 'face_tokens': [],\n",
       " 'face_count': 0,\n",
       " 'request_id': '1603431481,96e8f59c-89f5-4210-9ca3-039e5fc68b86',\n",
       " 'outer_id': '00001'}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet AddFace（增加人脸信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "AddFace_url = \" https://api-cn.faceplusplus.com/facepp/v3/faceset/addface\"\n",
    "\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'faceset_token':'37071d95016c1b2d81591a6f0c1681f2',\n",
    "    'face_tokens':'b0407b9e803ebd39d511cd7956fd5bf5',\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(AddFace_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'time_used': 71,\n",
       " 'error_message': 'INVALID_FACESET_TOKEN',\n",
       " 'request_id': '1603431660,d8e0217f-2328-415f-ac5d-a1e9c25c18c5'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet RemoveFace（移除人脸信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "RemoveFace_url = \" https://api-cn.faceplusplus.com/facepp/v3/faceset/removeface\"\n",
    "\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'faceset_token':'37071d95016c1b2d81591a6f0c1681f2',\n",
    "    'face_tokens':'b0407b9e803ebd39d511cd7956fd5bf5',\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(RemoveFace_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'time_used': 65,\n",
       " 'error_message': 'INVALID_FACESET_TOKEN',\n",
       " 'request_id': '1603431915,3da427af-569c-4a9d-a508-211a735451f2'}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FaceSet Update（更新人脸集合信息）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "Update_url = \"https://api-cn.faceplusplus.com/facepp/v3/faceset/update\"\n",
    "\n",
    "payload = {\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'faceset_token':'37071d95016c1b2d81591a6f0c1681f2',\n",
    "    'user_data':\"53人，21男生，32女生\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(Update_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'time_used': 70,\n",
       " 'error_message': 'INVALID_FACESET_TOKEN',\n",
       " 'request_id': '1603432104,a73fa86c-2ea5-428a-ab8a-a95df7ff9636'}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compare Face（对比人脸相似度）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "liudehua01 = \"https://gss0.baidu.com/9fo3dSag_xI4khGko9WTAnF6hhy/zhidao/pic/item/7c1ed21b0ef41bd57f7f20ff57da81cb39db3d89.jpg\"\n",
    "liudehua02 = \"https://tse3-mm.cn.bing.net/th/id/OIP.Xz3HbYZeNrdUnGJ7vXNzsQHaKO?pid=Api&rs=1\"\n",
    "wangzulan = \"https://tse3-mm.cn.bing.net/th/id/OIP.ZnXeGoVYT4jQudiPOGZn3QAAAA?pid=Api&rs=1\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 方案1:直接对比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "Compare_url = \"https://api-cn.faceplusplus.com/facepp/v3/compare\"\n",
    "\n",
    "payload ={\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'image_url1':liudehua01,\n",
    "    'image_url2':wangzulan\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(Compare_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'faces1': [{'face_rectangle': {'width': 824,\n",
       "    'top': 871,\n",
       "    'left': 1114,\n",
       "    'height': 824},\n",
       "   'face_token': 'a1dabce83c86b20b68dcea537eae57c5'}],\n",
       " 'faces2': [{'face_rectangle': {'width': 86,\n",
       "    'top': 91,\n",
       "    'left': 65,\n",
       "    'height': 86},\n",
       "   'face_token': '359ace131af5848047ff86b4bd521c66'}],\n",
       " 'time_used': 1883,\n",
       " 'thresholds': {'1e-3': 62.327, '1e-5': 73.975, '1e-4': 69.101},\n",
       " 'confidence': 26.085,\n",
       " 'image_id2': 'g6kg8zfyOouG6ftP+GvEfg==',\n",
       " 'image_id1': 'KIOXEC2V/MyL4zuopAcNig==',\n",
       " 'request_id': '1603432253,b0865971-7335-412b-bd8e-4857234b249f'}"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 方案2:与人脸集合进行对比"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 面部检测(获取face_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "Detect_url = 'https://api-cn.faceplusplus.com/facepp/v3/detect' \n",
    "img_url = liudehua01\n",
    "\n",
    "payload = {\n",
    "    \"image_url\":img_url,\n",
    "    'api_key': api_key,\n",
    "    'api_secret': api_secret,\n",
    "    'return_attributes':'gender,age,smiling,emotion', \n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = requests.post(Detect_url,params=payload)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'request_id': '1603432398,b494273f-c183-43bc-b5c3-82989e2187c6',\n",
       " 'time_used': 1488,\n",
       " 'faces': [{'face_token': '4ff18bc16a8e9664cc44a60aa3d7493e',\n",
       "   'face_rectangle': {'top': 871, 'left': 1114, 'width': 824, 'height': 824},\n",
       "   'attributes': {'gender': {'value': 'Male'},\n",
       "    'age': {'value': 59},\n",
       "    'smile': {'value': 99.998, 'threshold': 50.0},\n",
       "    'emotion': {'anger': 0.0,\n",
       "     'disgust': 0.047,\n",
       "     'fear': 0.0,\n",
       "     'happiness': 99.945,\n",
       "     'neutral': 0.0,\n",
       "     'sadness': 0.007,\n",
       "     'surprise': 0.0}}}],\n",
       " 'image_id': 'KIOXEC2V/MyL4zuopAcNig==',\n",
       " 'face_num': 1}"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 加入人脸集合"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 人脸识别社会/政治使用思考\n",
    "> 人脸识别的 API比较\n",
    ">> * [Face Off: Confronting Bias in Face Recognition AI](https://www.kairos.com/blog/face-off-confronting-bias-in-face-recognition-ai)\n",
    ">> * [为什么世界现在需要道德的面部识别](https://www.kairos.com/blog/why-the-world-needs-ethical-facial-recognition-now)\n",
    "    * 到2023年，全球人脸识别市场的价值估计接近100亿美元，复合年增长率为16.8％。市场背后的主要增长动力是监视市场的发展以及生物识别技术领域的政府支出。但是，面部识别的使用在其他领域也有很大贡献，例如帮助企业打击消费者欺诈，满足动态法规遵从性以及提供可获利的客户体验。\n",
    "\n",
    "-----\n",
    "> 人脸识别的偏差及API 政治经济学 \n",
    ">> * [对抗：面对面部识别AI中的偏见](https://www.kairos.com/blog/face-off-confronting-bias-in-face-recognition-ai)\n",
    "    * 发生了什么？\n",
    "        * “编码注视”或算法偏差的研究: 浅肤色男性的错误率为0.8％ ?  深色皮肤女性的错误率高达34.7％  ? (Microsoft，IBM和Face ++)\n",
    "    * 用户的反应范围从惊奇和赞美到不悦和冒犯\n",
    "        * 我们承认目前提供的种族分类（黑人，白人，亚裔，西班牙裔，其他则不足以代表丰富多样，发展迅速的文化和种族挂毯\n",
    "    * 该怎么办？\n",
    "        * 改善数据\n",
    "        * 寻求持续的反馈    \n",
    "        \n",
    ">>  * [科技行业没有应对面部识别偏见的计划](https://www.theverge.com/2018/7/26/17616290/facial-recognition-ai-bias-benchmark-test) \n",
    ">>> 公司在做什么？(一些高科技大公司支持基准和法规)     \n",
    ">>> 我们如何解决偏见问题？    \n",
    ">>> 偏差不是唯一的问题\n",
    "\n",
    ">> * [面部识别尚未准备好给执法部门使用](https://techcrunch.com/2018/06/25/facial-recognition-software-is-not-ready-for-use-by-law-enforcement/)\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 计算机视觉\n",
    "\n",
    "* 学习并完成所有Azure computer version 的API调用\n",
    "> * 分析远程图像    \n",
    "> * 分析本地图片    \n",
    "> * 生成缩略图    \n",
    "> * 提取印刷体文本和手写文本    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析远程图像"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"categories\": [{\"name\": \"building_\", \"score\": 0.77734375, \"detail\": {\"landmarks\": []}}, {\"name\": \"outdoor_\", \"score\": 0.00390625, \"detail\": {\"landmarks\": []}}], \"color\": {\"dominantColorForeground\": \"Blue\", \"dominantColorBackground\": \"Blue\", \"dominantColors\": [\"Blue\"], \"accentColor\": \"09458A\", \"isBwImg\": false, \"isBWImg\": false}, \"description\": {\"tags\": [\"outdoor\", \"building\", \"water\", \"light\", \"large\", \"city\", \"front\", \"tower\", \"clock\", \"sitting\", \"street\", \"boat\", \"tall\", \"green\", \"lit\", \"traffic\", \"standing\", \"parked\", \"ocean\", \"night\", \"river\", \"flying\", \"blue\", \"sign\", \"group\", \"kite\", \"beach\"], \"captions\": [{\"text\": \"a large tower in a city\", \"confidence\": 0.7080765374550395}]}, \"requestId\": \"056225a6-3cf6-4543-8bf4-39390a6112e7\", \"metadata\": {\"height\": 1200, \"width\": 1920, \"format\": \"Jpeg\"}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import requests\n",
    "# If you are using a Jupyter notebook, uncomment the following line.\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import json\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "# Add your Computer Vision subscription key and endpoint to your environment variables.\n",
    "# if 'COMPUTER_VISION_SUBSCRIPTION_KEY' in os.environ:\n",
    "#     subscription_key = os.environ['COMPUTER_VISION_SUBSCRIPTION_KEY']\n",
    "# else:\n",
    "#     print(\"\\nSet the COMPUTER_VISION_SUBSCRIPTION_KEY environment variable.\\n**Restart your shell or IDE for changes to take effect.**\")\n",
    "#     sys.exit()\n",
    "\n",
    "endpoint = \"https://shijue01.cognitiveservices.azure.com/\"\n",
    "# if 'COMPUTER_VISION_ENDPOINT' in os.environ:\n",
    "#     endpoint = os.environ['COMPUTER_VISION_ENDPOINT']\n",
    "whf_key = \"8a2abe4e786c40c1936efe083f794112\"\n",
    "\n",
    "# base url\n",
    "analyze_url = endpoint+ \"vision/v2.1/analyze\"\n",
    "\n",
    "# Set image_url to the URL of an image that you want to analyze.\n",
    "image_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603444862064&di=a64f57fc7d2973009b1ae8d538bf09d9&imgtype=0&src=http%3A%2F%2Fpic1.win4000.com%2Fwallpaper%2F2018-09-10%2F5b95d4a16d7d4.jpg\"\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': whf_key}\n",
    "# 参数\n",
    "params = {'visualFeatures': 'Categories,Description,Color'}\n",
    "# 请求主体bodyk\n",
    "data = {'url': image_url}\n",
    "response = requests.post(analyze_url, headers=headers,params=params, json=data)\n",
    "response.raise_for_status()\n",
    "\n",
    "# The 'analysis' object contains various fields that describe the image. The most\n",
    "# relevant caption for the image is obtained from the 'description' property.\n",
    "analysis = response.json()\n",
    "print(json.dumps(response.json()))\n",
    "image_caption = analysis[\"description\"][\"captions\"][0][\"text\"].capitalize()\n",
    "\n",
    "# Display the image and overlay it with the caption.\n",
    "image = Image.open(BytesIO(requests.get(image_url).content))\n",
    "plt.imshow(image)\n",
    "plt.axis(\"off\")\n",
    "_ = plt.title(image_caption, size=\"x-large\", y=-0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析本地图片"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'categories': [{'name': 'others_', 'score': 0.00390625}, {'name': 'outdoor_', 'score': 0.0078125, 'detail': {'landmarks': []}}], 'color': {'dominantColorForeground': 'Blue', 'dominantColorBackground': 'Grey', 'dominantColors': ['Grey', 'Blue'], 'accentColor': '203F6D', 'isBwImg': False, 'isBWImg': False}, 'description': {'tags': ['outdoor', 'snow', 'nature', 'water', 'tree', 'man', 'covered', 'standing', 'skiing', 'field', 'beach', 'clouds', 'sun', 'riding', 'people', 'hill', 'mountain', 'flying', 'slope', 'air', 'walking', 'woman', 'ocean', 'sunset', 'group', 'board', 'sand'], 'captions': [{'text': 'a tree covered in snow', 'confidence': 0.8273600224194236}]}, 'requestId': 'fad9519a-bc67-41fc-a375-435c9132fedc', 'metadata': {'height': 313, 'width': 500, 'format': 'Jpeg'}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "import requests\n",
    "# If you are using a Jupyter notebook, uncomment the following line.\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "# Add your Computer Vision subscription key and endpoint to your environment variables.\n",
    "# if 'COMPUTER_VISION_SUBSCRIPTION_KEY' in os.environ:\n",
    "#     subscription_key = os.environ['COMPUTER_VISION_SUBSCRIPTION_KEY']\n",
    "# else:\n",
    "#     print(\"\\nSet the COMPUTER_VISION_SUBSCRIPTION_KEY environment variable.\\n**Restart your shell or IDE for changes to take effect.**\")\n",
    "#     sys.exit()\n",
    "\n",
    "# if 'COMPUTER_VISION_ENDPOINT' in os.environ:\n",
    "#     endpoint = os.environ['COMPUTER_VISION_ENDPOINT']\n",
    "\n",
    "# analyze_url = endpoint + \"vision/v2.1/analyze\"\n",
    "\n",
    "# Set image_path to the local path of an image that you want to analyze.\n",
    "image_path = '/Users/86132/Desktop/学习文件/API/api_week5_work/本地图片.jpg'\n",
    "# Read the image into a byte array\n",
    "image_data = open(image_path, \"rb\").read()\n",
    "headers = {'Ocp-Apim-Subscription-Key': \"8a2abe4e786c40c1936efe083f794112\",\n",
    "           'Content-Type': 'application/octet-stream'}\n",
    "params = {'visualFeatures': 'Categories,Description,Color'}\n",
    "response = requests.post(\n",
    "    analyze_url, headers=headers, params=params, data=image_data)\n",
    "response.raise_for_status()\n",
    "\n",
    "# The 'analysis' object contains various fields that describe the image. The most\n",
    "# relevant caption for the image is obtained from the 'description' property.\n",
    "analysis = response.json()\n",
    "print(analysis)\n",
    "image_caption = analysis[\"description\"][\"captions\"][0][\"text\"].capitalize()\n",
    "\n",
    "# Display the image and overlay it with the caption.\n",
    "image = Image.open(BytesIO(image_data))\n",
    "plt.imshow(image)\n",
    "plt.axis(\"off\")\n",
    "_ = plt.title(image_caption, size=\"x-large\", y=-0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 生成缩略图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Thumbnail is 100-by-100\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "import requests\n",
    "# If you are using a Jupyter notebook, uncomment the following line.\n",
    "# %matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "# Add your Computer Vision subscription key and endpoint to your environment variables.\n",
    "# if 'COMPUTER_VISION_SUBSCRIPTION_KEY' in os.environ:\n",
    "#     subscription_key = os.environ['COMPUTER_VISION_SUBSCRIPTION_KEY']\n",
    "# else:\n",
    "#     print(\"\\nSet the COMPUTER_VISION_SUBSCRIPTION_KEY environment variable.\\n**Restart your shell or IDE for changes to take effect.**\")\n",
    "#     sys.exit()\n",
    "\n",
    "# if 'COMPUTER_VISION_ENDPOINT' in os.environ:\n",
    "#     endpoint = os.environ['COMPUTER_VISION_ENDPOINT']\n",
    "\n",
    "thumbnail_url = \"https://api-computervvsion-cyl.cognitiveservices.azure.com/\" + \"vision/v2.1/generateThumbnail\"\n",
    "\n",
    "# Set image_url to the URL of an image that you want to analyze.\n",
    "image_url = \"https://ss3.bdstatic.com/70cFv8Sh_Q1YnxGkpoWK1HF6hhy/it/u=2096015808,1580004639&fm=26&gp=0.jpg\"\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': \"dd748cf10bf9404399e5416d9399e218\"}\n",
    "params = {'width': '100', 'height': '100', 'smartCropping': 'true'}\n",
    "data = {'url': image_url}\n",
    "response = requests.post(thumbnail_url, headers=headers,\n",
    "                         params=params, json=data)\n",
    "response.raise_for_status()\n",
    "\n",
    "thumbnail = Image.open(BytesIO(response.content))\n",
    "\n",
    "# Display the thumbnail.\n",
    "plt.imshow(thumbnail)\n",
    "plt.axis(\"off\")\n",
    "\n",
    "# Verify the thumbnail size.\n",
    "print(\"Thumbnail is {0}-by-{1}\".format(*thumbnail.size))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 提取印刷体文本和手写文本 \n",
    "* 假如我们抓取了1000张网页，出了文本信息我们分析以外，还有每个页面的图片的信息，我们可以用提取图片文本的方式，将图片的信息也抓取下来\n",
    "* 我们进抓取了图片，想知道这些图片的内容是什么，也可以用提取文本的方式进行提取\n",
    "* ...."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'result': {'landmarks': [{'name': 'Leaning Tower of Pisa', 'confidence': 1.0}]}, 'requestId': '9cb7f985-a2fb-4989-9733-5beaddde2741', 'metadata': {'height': 1280, 'width': 1250, 'format': 'Jpeg'}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "import requests\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "from io import BytesIO\n",
    "\n",
    "landmark_analyze_url = endpoint + \"vision/v3.1/models/landmarks/analyze\"\n",
    "\n",
    "# Set image_url to the URL of an image that you want to analyze.\n",
    "image_url = \"https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1603464156547&di=474b33d715dedb989807b13961f33369&imgtype=0&src=http%3A%2F%2Fyouimg1.c-ctrip.com%2Ftarget%2F10040k000000c77ziAC41.jpg\"\n",
    "\n",
    "headers = {'Ocp-Apim-Subscription-Key': \"8a2abe4e786c40c1936efe083f794112\"}\n",
    "params = {'model': 'landmarks'}\n",
    "data = {'url': image_url}\n",
    "response = requests.post(\n",
    "    landmark_analyze_url, headers=headers, params=params, json=data)\n",
    "response.raise_for_status()\n",
    "\n",
    "# The 'analysis' object contains various fields that describe the image. The\n",
    "# most relevant landmark for the image is obtained from the 'result' property.\n",
    "analysis = response.json()\n",
    "assert analysis[\"result\"][\"landmarks\"] is not []\n",
    "print(analysis)\n",
    "landmark_name = analysis[\"result\"][\"landmarks\"][0][\"name\"].capitalize()\n",
    "\n",
    "# Display the image and overlay it with the landmark name.\n",
    "image = Image.open(BytesIO(requests.get(image_url).content))\n",
    "plt.imshow(image)\n",
    "plt.axis(\"off\")\n",
    "_ = plt.title(landmark_name, size=\"x-large\", y=-0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 学习人脸识别和计算机视觉心得体会\n",
    "\n",
    "> 历程艰辛！    \n",
    "> 不会放弃！    \n",
    "> 终得成果！    \n",
    "> 分享经验吧～"
   ]
  }
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